Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/66160
Title: A lamb wave-based crack diagnosis method using an improved RAPID algorithm
Authors: Wang, Q
Wang, M
Yue, D
Su, Z 
Keywords: Crack detection
Lamb wave
Orientation and length
RAPID algorithm
Structural health monitoring
Issue Date: 2016
Publisher: NDT.net
Source: 8th European Workshop on Structural Health Monitoring, EWSHM 2016, 2016, v. 2, p. 1162-1171 How to cite?
Abstract: Crack is one of the most typical damage types in engineering structures, and therefore is a research focus in the field of structural health monitoring (SHM). The monitoring and evaluation methods for crack-Type damage are studied using a Lamb wave-based RAPID algorithm (Reconstruction Algorithm for the Probabilistic Inspection of Damage) in this study, which is based on a correlation analysis. RAPID algorithm can overcome the shortcomings of the complex signal analysis affected by multimode nature of Lamb waves. The improved RAPID algorithm is proposed to reconstruct the tomographic image of the crack-Type damage by correcting the Signal Difference Coefficient (SDC) of the sensing path at the crack direction based on the Lamb wave reflection and scattering principle at the crack. The orientation of the crack can be enriched after the correction so that it can be highlighted in the reconstructed image. Furthermore, the length of the crack can be evaluated by the SDC distribution map. The experiments were carried out to validate the improved method and results shown that the reconstructed tomographic images can indicate the crack damage quantitatively. The orientation of artificial crack damages were revealed with minor errors and the length of the damages were also evaluated. The experimental results have stressed that the proposed method is effective for crack damage quantitative evaluation and monitoring of crack growth.
Description: 8th European Workshop on Structural Health Monitoring, EWSHM 2016, Spain, 5-8 July 2016
URI: http://hdl.handle.net/10397/66160
ISBN: 9781510827936
Appears in Collections:Conference Paper

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